Cost-effectiveness analysis is a well recognized tool to support decisions about resource allocation in healthcare, particularly in the context of collectively funded health systems. When a new technology is restricted based on cost-effectiveness (because it is deemed too expensive relative to its expected benefits) a potential conflict can arise between the social interests (i.e. maximization of the population health subject to fixed budget constraint) and individuals who want to maximize their own health or utility. It has been previously argued that decisions that consider heterogeneity add value to the healthcare system. On the one hand, if a centralized decision process is implemented (e.g. NICE in the UK), subgroup analysis is appropriate. On the other hand, if a decentralized process is to be implemented, the effect of unrestricted choices on the social interests must be assessed. I have recently presented an analytical approach to estimate the expected health forgone (or gained) as a consequence of implementing a decentralized decision process. In the simplest case it was assumed that social planners and patients focus on the same metric of health, i.e. patients maximise health (for example, QALYs) and social decision makers maximise net health (net QALYs). This piece of work examines the case where patients choose according to a different maximand. The analysis shows that if a single and different argument of the patient’s maximization function can be identified, the expected net health benefits forgone (or gained) from implementing unrestricted choices can be estimated as an extension of the base-case analysis. It also highlights the role of a robust estimation of the joint distribution of potential outcomes, discussing gaps that require further research. The contribution of this analysis for policy decisions about individualized care is illustrated with a stylized numerical example.